AB0254 ASSOCIATED FACTORS WITH TREATMENT ADHERENCE IN RHEUMATOID ARTHRITIS: A CROSS-SECTIONAL ANALYTIC STUDY OF COLOMBIAN PATIENTS.
Authors: E. Cubillos Escobar, K. Maldonado-Cañón, P. Coral Alvarado, P. A. Mendez Patarroyo, W. Bautista-Molano, G. Quintana Lopez
Journal: Annals of the Rheumatic Diseases (2022)

Background Rheumatoid arthritis (RA) represents an essential public health problem regarding vast influence on the individual’s global health. Adherence to pharmacological therapy has been shown to be a relevant outcome to ensure the desired therapeutic objectives and thus avoid the recurring concern of flares, the perpetuation of inflammation, and its consequences, not only physiological but also structural and socioeconomic. Objectives Our aim was to identify clinical-epidemiological variables associated with treatment adherence in an outpatient clinic-based cohort of Colombian RA patients. Methods We conducted a cross-sectional analytic study with data obtained from August 2020 to October 2021. Treatment adherence was assessed on each visit through the Compliance Questionnaire on Rheumatology (CQR); moreover, patients were stratified into those who were adherent to the treatment and those who didn’t, according to their CQR score. Additional information regarding the quality of life (QOL-RA), disease activity (DAS28 ESR), and functionality (HAQ) was recovered from electronic clinical charts. Data was gathered on a database stored in REDCap. T-test and Chi-squared test were used for comparisons and a multiple logistic regression with backward selection was performed to build the final fitted model. Results Data from a total of 564 patients were included in the analysis. Our population was constituted of 79.1% women with a mean age of 53 (± 13.1); the CQR mean score was 77.7 (± 9.26) and treatment adherence, defined as a CQR score of ≥ 80.7, was seen in 49.3% of the cases. Mean DAS28 ESR, QOL-RA, and HAQ scores were 3.3 (± 1.62), 7.24 (± 1.43), and 0.671 (± 0.716), respectively; with a reported preserved quality of life (QOL-RA &gt;7) in 60,5% of patients. Monotherapy (42.7%) and combined therapy (49-6%) were the two most common treatment schemes, being MTX the more frequent DMARD (58.9% oral, 20.9% subcutaneous). Noncompliant patients showed higher mean disease activity (3.52 (±1.66) vs 3.08 (±1.54); p 0.001) and lower quality of life (6.94 (±1.43) vs 7.56 (±1.35); p &lt;0.001) scores. Having a higher DAS28 score (OR 1,19), drug dispensing delay (OR: 1,71), and infection as an adverse effect (OR 2.53) were recognized as risk factors for an impaired treatment adherence after adjustment for the effects of possible confounders. Complete results of the multiple logistic regression model are shown in Table 1. Table 1. Associated factors with treatment adherence in RA patients. Odds Ratio (95% Confidence Interval ) p-value Age 0,99 (0,97 – 1) 0,12 Male 1,54 (0,98 – 2,43 ) 0,065 Having a stable partner 0,75 (0,52 – 1,09) 0,13 Comorbidities Hypothyroidism 0,69 (0,41 – 1,15) 0,16 Dyslipidemia 0,52 (0,22 – 1,16) 0,12 Dyspepsia (AE ) 1,48 (0,97 – 2,28 ) 0,07 Infection (AE ) 2,53 (1,31 – 5,08 ) 0,007 Perception of the information received by health professionals 0,45 Unsatisfied Ref. Satisfied 2,23 (0,06 – 28,1) 0,55 Very satisfied 1,37 (0,09 – 17,2) 0,81 Healthcare barriers 1,98 (0,92 – 4,45 ) 0,088 Drug dispensing delay 1,71 (0,99 – 2,99 ) 0,058 Disease duration (months) until rheumatology consultation 1,00 (0,99 – 1,00 ) 0,004 DAS28 ESR score 1,19 (1,06 – 1,33 ) 0,003 AE: adverse effect. Bold values indicate a p value &lt; 0,1 Conclusion In our study population, there were evident trends regarding the effects of dispensing delays, adverse effects, and barriers to access to the health system on reducing treatment adherence. Moreover, there was a subtle association of treatment adherence with the DAS28 score, as well as with a better quality of life. Taken together, these results suggest the need for the implementation of educational programs that will support a comprehensive approach that considers not only patient-related factors but also the proper functioning of the healthcare system itself. Further research with a follow-up period could assess the long-term effects on several clinical outcomes and explore if proposed trends change with time. Figure 1. Density plot comparing disease activity in patients that are compliant and noncompliant to treatment. Disclosure of Interests None declared